research

Collaborative Disagreement Resolution for Scalable Oversight

arXiv:2607.01251v1 Announce Type: cross Abstract: Debate, where AI agents argue opposing positions, has emerged as a key approach to scalable oversight. However, debate faces a fundamental tension: mo

Combating Textual Noise and Redundancy: Entropy-Aware Dense Visual Token Pruning

DGX agent

arXiv:2607.02484v1 Announce Type: cross Abstract: Visual token pruning is a crucial strategy for accelerating VLMs by compressing redundant image patches, yet existing methods often fail to preserve c

researcharxiv-cs-ai

3 Jul 2026

Comparing Architectures for Supervised Political Scaling

arXiv:2607.01464v1 Announce Type: new Abstract: Text scaling, the task of positioning political actors on an ideological scale, is a fundamental task in political analysis. To ease the need for manual

researcharxiv-cs-cl

Conditional Co-Ablation: Recovering Self-Repair Backups in Transformer Circuits

arXiv:2607.01940v1 Announce Type: cross Abstract: Mechanistic interpretability often relies on component-level interventions to discover how a model produces a behavior. This guides attribution, capab

Contrastive Deep Learning Reveals Age Biomarkers in Histopathological Skin Biopsies

arXiv:2411.16956v2 Announce Type: replace-cross Abstract: As global life expectancy increases, so does the burden of chronic diseases, yet individuals exhibit considerable variability in the rate at w

CreativityNeuro: Steering Language Model Weights to Improve Divergent Thinking and Reduce Mode Collapse

arXiv:2607.01433v1 Announce Type: new Abstract: Divergent thinking is a crucial aspect of creativity, yet large language models (LLMs) tend to consistently generate similar responses to open-ended que

DL-SLAM: Enabling High-Fidelity Gaussian Splatting SLAM in Dynamic Environments based on Dual-Level Probability

arXiv:2607.01860v1 Announce Type: new Abstract: Recent advances in 3D Gaussian Splatting (3DGS) have enabled significant progress in dense dynamic Simultaneous Localization And Mapping (SLAM). Prevail

researcharxiv-cs-ro

Do LLMs Truly Generalize in the Molecular Domain? A Perturbation-Based Analysis

arXiv:2607.01800v1 Announce Type: cross Abstract: Large Language Models (LLMs) have recently shown promise in molecular discovery, yet a gap remains between their probabilistic nature over discrete se

researcharxiv-cs-cl

DRIFTLENS: Measuring Memory-Induced Reasoning Drift in Personalized Language Models

arXiv:2607.02374v1 Announce Type: new Abstract: Personalization changes what a model says to a user; we show that it can also change the reasoning trajectory used to justify the response. Modern LLMs

Dynamic Neural Graph Encoding of Inference Processes in Deep Weight Space

arXiv:2607.02166v1 Announce Type: cross Abstract: The rapid advancements in using neural networks as implicit data representations have attracted significant interest in developing machine learning me

Embedding Inference Attack

arXiv:2607.01276v1 Announce Type: cross Abstract: Embedding models are essential components of modern Information Retrieval (IR) systems, yet they are typically hidden behind APIs. Recent works have s

Enhancing Fitness Intelligence through Domain-Specific LLM Post-Training

arXiv:2607.02118v1 Announce Type: new Abstract: Scientific Fitness Coaching (SFC) is typically delivered by human professionals, making it costly and inaccessible to many. While recent advances in Lar

Estimating Individualized Treatment Effects in Acute Ischemic Stroke with Causal Transformation Models (TRAM-DAG): A Multi-Centre Observational Study with External RCT Validation

arXiv:2606.12623v3 Announce Type: replace-cross Abstract: Personalized medicine in acute ischemic stroke requires moving beyond average treatment effects (ATE) to individualized treatment effect (ITE)

Evaluating Chunking Strategies for Retrieval-Augmented Generation on Academic Texts

arXiv:2607.01852v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) systems use the question-answering capabilities of Large Language Models (LLMs) to access information outside the

Evolutionary Feature Engineering for Structured Data

arXiv:2607.01548v1 Announce Type: cross Abstract: Large language models are increasingly used as open-ended search operators in evolutionary optimization. We introduce Evolutionary Feature Engineering

Exactly. I've been disseminating a similar message for years. The concentration of power in AI and the desire for control is by far the bigg…

Exactly. I've been disseminating a similar message for years. The concentration of power in AI and the desire for control is by far the biggest danger of AI. It could lead to a few private companies a

researchyann-lecun--x

ExPerT: Personalizing LLM Responses to Users' Domain Expertise via Query-Wise Semantic and Keystroke Behavioral Cues

arXiv:2607.01242v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used by end users, yet existing personalization methods relying on static profiles or text-only signals

Fast approximation and learning of binary classification tasks in o-minimal structures using ReLU neural networks

arXiv:2607.01266v1 Announce Type: cross Abstract: We study binary classification problems whose decision sets are given by definable sets in o-minimal expansions of the real field. Motivated by cell d

Few-Shot Open-Set Audio Classification Using Attention Information-Fused Prototypes

arXiv:2607.01297v1 Announce Type: cross Abstract: Most existing audio classification methods suppose that each query (testing) sample belongs to a class of support (training) samples, and misrecognize

Finite-Lag Operator Geometry of Recurrent Representations

arXiv:2607.01746v1 Announce Type: new Abstract: Recurrent representations are trajectories, but representation geometry is often measured from static snapshots. We develop finite-lag operator geometry

Fourier Neural Operators for Rayleigh-Benard Convection

arXiv:2607.02088v1 Announce Type: new Abstract: We propose an improved Fourier Neural Operator (FNO) for modeling two-dimensional Rayleigh-Benard convection by predicting time increments instead of fu

Fourier Preconditioning for Neural Feature Learning

arXiv:2607.02199v1 Announce Type: cross Abstract: Mutual information (MI)-inspired feature learning techniques are capable of generating low-dimensional embeddings that retain nonlinear dependence str

From Experiments to Expertise: Scientific Knowledge Consolidation for AI-Driven Computational Physics

arXiv:2603.13191v2 Announce Type: replace-cross Abstract: While large language models (LLMs) have transformed AI agents into proficient executors of computational materials science, performing a hundr

Fully Unsupervised Detection of Physical Contacts on Subsea Cables via State-of-Polarization Monitoring

arXiv:2607.01484v1 Announce Type: cross Abstract: We present a fully unsupervised Fast-Slow DSVDD detector for continuous State-of-Polarization monitoring on a deployed subsea cable. Trained without e

Game Physics Just Got 170 Times Faster

researchtwo-minute-papers

This video from Two Minute Papers discusses groundbreaking research by NVIDIA that achieves a 100x speedup in physics-based character animations using AI-powered super-resolution applied to physics si

Gender Differences in Research Topic and Method Selection in Library and Information Science: Perspectives from Three Top Journals

arXiv:2607.01828v1 Announce Type: cross Abstract: Research in the social sciences has shown that there are gender differences in the selection of research methods, with women often opting for qualitat

researcharxiv-cs-cl

Geometric Signatures of Reasoning: A Spectral Perspective on Task Hardness

arXiv:2607.01571v1 Announce Type: new Abstract: Chain-of-thought (CoT) reasoning enables large language models (LLMs) to solve complex problems by generating intermediate reasoning steps. While much a

Geometry as a Missing Axis of Representation Quality: The Variational Geometric Information Bottleneck under Data Scarcity

arXiv:2511.02496v2 Announce Type: replace Abstract: We study latent geometry as an explicit component of representation quality in data-scarce learning. For an encoder (phi), we define (Q_{eta,gamma}(

Geometry-Aware R-Structured Kolmogorov-Arnold Networks

arXiv:2607.01449v1 Announce Type: new Abstract: We propose a novel hybrid neural architecture, the Geometry-aware R-Structured Kolmogorov-Arnold Network (GRS-KAN), which integrates V.L.Rvachev's R-fun

Hamm-Grams: An Algorithm for Mining Regular Expressions of Bytes

arXiv:2607.01445v1 Announce Type: cross Abstract: Malware poses a critical and ever-evolving threat, and robust and effective systems for detecting and classifying malware are of essential importance.

Happy Independence Day, from Tokyo 🇺🇸

David Ha shares a greeting celebrating American Independence Day from Tokyo, Japan. The post likely combines holiday wishes with Ha's perspective as someone observing or living in Japan. This brief so

researchdavid-ha--x

Hidden Forgetting in Continual Multimodal Learning: When Accuracy Survives but Grounding Fails

arXiv:2607.02020v1 Announce Type: new Abstract: Multimodal large language models must continually adapt to evolving tasks and domains, yet standard continual learning metrics mainly measure whether ol

High-Dimensional Change Point Detection via Graph Spanning Ratio

arXiv:2512.07541v3 Announce Type: replace-cross Abstract: Inspired by graph-based methodologies, we introduce a novel graph-spanning algorithm designed to identify changes in both offline and online d

Horizon-Uniform Sensitivity Certificates for Finite-Horizon Pontryagin Systems

arXiv:2606.17762v2 Announce Type: replace-cross Abstract: Finite-horizon optimal-control computations repeatedly solve two-point Pontryagin boundary value problems whose conditioning can deteriorate a

How Indian Dermatologists are Utilizing Artificial Intelligence for Clinical Practice and Workflow Management: A Nationwide Survey with a Special Focus on atopic dermatitis

arXiv:2607.01252v1 Announce Type: cross Abstract: Background: Dermatology AI has mainly focused on image-based diagnosis, while chronic disease workflows have received less attention. We surveyed Indi

Human Supervisor Workload Prediction: Lag Horizon Selection

arXiv:2505.15939v2 Announce Type: replace Abstract: Teleoperation systems must be aware of the human's workload during missions to maintain operator performance. Prior work employed wearable physiolog

researcharxiv-cs-ro

Hybrid quantum-classical neural network for sentiment analysis

arXiv:2607.01943v1 Announce Type: new Abstract: Quantum machine learning has recently emerged as a promising paradigm that leverages the expressive power of quantum circuits to address complex learnin

I spent a LOT of time through the hardest 3D prompts at Fable, it is a 45 min video, but I have 60+ very cool demos for you. Also prompts in…

Andrej Karpathy shared a comprehensive 45-minute video demonstrating over 60 advanced 3D prompting techniques and examples using Fable, along with the actual prompts used. The content covers challengi

researchkarpathy--x

Iextsuperscript{2}RiMA: Spectral Riemannian Representation with Temporal Attention for Mental Stress Detection based on EEG Signals

arXiv:2607.01279v1 Announce Type: new Abstract: Cross-subject EEG stress detection remains challenging because discriminative stress-related patterns are both subject-dependent and frequency-specific.

In retrospect... Yep

researchfrancois-chollet--x

In retrospect... Yep One very important thing to understand about the future: the economics of AI are about to change completely. We'll soon be in a world where you can turn test-time compute into com

Incremental (k, z)-Clustering on Graphs

arXiv:2602.08542v3 Announce Type: replace-cross Abstract: Given a weighted undirected graph, a number of clusters k, and an exponent z, the goal in the (k, z)-clustering problem on graphs is to select

Interpreting Global Perturbation Robustness of Image Models using Axiomatic Spectral Importance Decomposition

arXiv:2408.01139v4 Announce Type: replace Abstract: Perturbation robustness evaluates the vulnerabilities of models, arising from a variety of perturbations, such as data corruptions and adversarial a

Introduction to Transformers: an NLP Perspective

arXiv:2311.17633v2 Announce Type: replace-cross Abstract: Transformers have dominated empirical machine learning models of natural language processing. In this paper, we introduce basic concepts of Tr

I’ve been asked many times over why I keep posting when so many of the replies I receive are personal attacks. The answer is actually really…

I’ve been asked many times over why I keep posting when so many of the replies I receive are personal attacks. The answer is actually really simple. As scientists, we cannot concede to silence. If we

researchyann-lecun--x

Learning the Supports for Categorical Critic in Reinforcement Learning

arXiv:2607.01880v1 Announce Type: new Abstract: Value functions are an essential component in actor-critic based deep reinforcement learning (RL). Conventionally, these functions are trained as a regr

LLM Priors for ERM over Programs

arXiv:2510.14331v3 Announce Type: replace Abstract: We study program-learning methods that are efficient in both samples and computation. Classical learning theory suggests that when the target admits

Local exponential stability of mean-field Langevin descent-ascent and associated particle system

arXiv:2602.01564v2 Announce Type: replace Abstract: We study the mean-field Langevin descent-ascent (MFL-DA), a coupled optimization dynamics on the space of probability measures for entropically regu

Low-Latency Task-Oriented Image Transmission with Opportunistic Spectrum Access

arXiv:2607.01921v1 Announce Type: cross Abstract: Communication systems designed for reliable data reconstruction, rather than task-oriented communication, typically rely on separate source and channe